Application of numerical simulation method integrated SfM-UAV to tsunami hazard map in Jailolo

Abstract

Tsunamis pose a significant threat to the Jailolo coastal area in North Maluku, Indonesia, because of its proximity to the Maluku Sea subduction zone, where seismic activity has historically triggered destructive waves. This study aims to map tsunami hazards in the Jailolo coastal area by integrating the Structure-from-Motion (SfM) photogrammetry method with numerical calculations. The SfM photogrammetry method involves using an unmanned aerial vehicle (UAV) to produce digital elevation model (DEM) data in the form of digital terrain model and digital surface model, as well as orthomosaic data. In addition, tsunami wave propagation simulation modelling was carried out using the Cornell Multi-Grid Coupled Tsunami computational program, with input data including Manning’s coefficient data and fault parameters. The aerial photography resulted in DEMs with a vertical accuracy of LE90 of 0.15 metres and an orthomosaic with a horizontal accuracy of CE90 of 0.5 metres. The tsunami simulation revealed tsunami waves reaching 5.8–17.4 metres, with a hazard zone of approximately 119.31 hectares and an inundation distance of about 700 metres from the coast. The affected areas include settlements, agriculture and mangrove forests. In conclusion, the integration of UAV-based SfM photogrammetry and numerical simulations effectively produces high-precision tsunami hazard maps.

Contribution: This study provides a significant contribution to disaster mitigation and evacuation planning by providing an accurate and efficient method for mapping tsunami hazards. The precise data can support decision-making in high-risk coastal areas such as Jailolo.